AI-Driven Store Replenishment Optimisation for a Leading UK Supermarket Retailer

One of the UK’s largest supermarket retailers partnered with SolvedBy.Ai to modernise store replenishment operations through intelligent scheduling and demand forecasting. Operating hundreds of stores nationwide, the retailer sought to improve efficiency during critical stock intake periods while also enhancing employee experience and operational consistency.
The initiative focused on transforming how replenishment tasks are allocated during high-volume delivery windows, replacing manual coordination with AI-driven optimisation.

The retailer faced increasing operational pressure around stock replenishment, particularly during early morning and afternoon intake periods. Managers needed a faster, smarter way to allocate tasks while balancing productivity, employee capability, and store priorities.

Key issues included:

SolvedBy.Ai introduced an AI-powered task scheduling and replenishment optimisation solution designed specifically for retail store operations.
Here’s how it works:

Intelligent Task Allocation

During stock intake periods at 3:00 a.m. and 3:00 p.m., store managers submit replenishment requests through the retailer’s internal app. The SolvedBy.Ai model automatically processes and allocates tasks according to agreed operational business rules.

Employee Performance Matching

The algorithm considers a range of operational and workforce factors, including:
- Employee performance history.
- Previous experience completing similar tasks.
- Individual preferences and working patterns.
- Task urgency and store priorities.
- Manager feedback and operational weighting factors.

To improve consistency and execution quality, priority tasks are only assigned to employees who have successfully completed the same task within the previous six months.

Smarter Operational Decision-Making
The solution continuously refines allocation logic to ensure stores can respond more efficiently during replenishment peaks while improving staff productivity and satisfaction.

Future-Ready Forecasting

Planned future enhancements will integrate real-time operational data such as:
- Live sales trends.
- Shelf availability.
- Warehouse inventory levels.
- Demand fluctuations across stores.

This will further optimise replenishment timing and labour allocation across the retail network.

The collaboration with SolvedBy.Ai has enabled the retailer to move toward a more intelligent, data-driven replenishment model, improving both operational execution and employee experience.

Key outcomes include:

The task scheduling model has already been adopted by the retailer and is currently being trialled in five stores, with plans to expand to an additional 95 stores during a four-week proof-of-concept phase.

The retailer can now:

A leading UK supermarket retailer with a heritage dating back to the late 19th century, the business has grown from a regional market stall into one of the country’s largest grocery chains, serving millions of customers each week through a nationwide network of supermarkets, convenience stores, and online channels.

Known for its strong focus on fresh food, vertically integrated supply chain, and in-house manufacturing capabilities, the retailer combines large-scale operations with a commitment to quality, value, and operational efficiency.

Today, the company continues to invest heavily in technology, automation, and data-driven innovation to improve store operations, workforce productivity, and customer experience across its retail estate.